The goal of this fellowship is for the applicant (Daniel S. Barron) to learn advanced neuroimaging research methods and to gain significant exposure to clinical epilepsy care. The applicant will receive training in structural, functional, and diffuion magnetic resonance image analysis methods; he will use these methods to quantify extra-hippocampal pathology in medial temporal lobe epilepsy (MTLE). MTLE is the most common type of epilepsy referred to surgical centers and the most common localization- related epilepsy in adults. (Tellez-Zenteno et al., 2012). The most common pathology in MTLE is hippocampal sclerosis (HS). (Wieser, 2004) When it is the sole pathology observed on visual inspection of magnetic resonance images, HS is a predictor of positive surgical outcome. (Engel, 2008) Conversely, extra-hippocampal pathology is a predictor of poorer outcome and is, in fact, a contraindication for surgery. (Thom et al., 2010) Extra-hippocampal pathology is often subtle and goes visually undetected on the pre-surgical evaluation, thus extra-hippocampal pathology continues to contribute to surgical failure. (Thom et al., 2010) Quantitative, targeted analyses of extrahippocampal pathology could guide the pre-surgical evaluation, inform new therapeutic interventions, and mitigate surgical failure. Thus far such attempts have met with limited success and represent a critical barrier to improved pre-surgical evaluation and patient care. Our immediate research goal is to define regions of extra-hippocampal pathology in MTLE-HS with the long- term goal of understanding surgical failure. Our recent meta-analysis of 24 voxel-based morphometry experiments (manuscript in review) demonstrated the most consistent area of extra-hippocampal pathology in MTLE is the medial dorsal nucleus of the thalamus (MDN). We hypothesize that MTLE is associated with selective tissue damage in the MDN related to increased functional and anatomical connectivity between the MDN and the hippocampus. To test this hypothesis we will perform the following analyses on MTLE-HS patient data: Aim 1. We will measure changes in MDN volume using structural MR data. Aim 2. We will measure anatomic connectivity in white matter tracts connecting the hippocampus and MDN using diffusion MR data. Aim 3. We will measure functional connectivity between the hippocampus and MDN using region-seeded analyses of resting-state functional MR data. To learn these neuroimaging analysis methods, the applicant will leverage intra-mural and extra-mural courses and collaborations. The applicant will also have clinical exposure to the pathophysiology, clinical care, and surgical treatment of MTLE. This research training will allow the applicant to learn neuroimaging analysis methods he will use as a neuroimaging researcher and epileptologist.